code: def forward_rnn(self, inputs, state, seq_lens):
      # Previously, a new class object was created during
      # deserialization and this `capture_index`
      # variable would be refreshed between class instantiations.
      # This behavior is no longer the case, so we manually refresh
      # the variable.
      RNNSpyModel.capture_index = 0
      model_out, value_out, h, c = self.base_model(
          [inputs, seq_lens, state[0], state[1]]
      )
      self._value_out = value_out
      return model_out, [h, c]
  
file_path: ray/python/ray/rllib/examples/models/rnn_spy_model.py
imports: import numpy
  import pickle
  import ray
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.tf.misc import normc_initializer
  from ray.rllib.models.tf.recurrent_net import RecurrentNetwork
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.framework import try_import_tf
label_desc: Use image node_id 2 for calling the RNNSpyModel obj's underlying member method code with example usage: obj.forward_rnn(inputs, state, seq_lens) and returns: model_out,  list